Drawn quickly and reflects more of the signer’s own personality, portraying dependencies of his or her neuromotor system’s ability and spatial cognitive map, among other factors. Also the text line design depends mainly on the signer’s name and the way the signers like to be introduced to others. For instance, let Peter Andrew Lee be a fictitious name. It could be written as P. A. Lee, Peter A. Lee and so on. The word and letter content defines the lexical part of a signature. Both parts give a particular structure or morphology to a signature. A number of disciplines require a deeper analysis of signatures for their specific fields of interests. Neurologists, graphologists, forensic and computer scientists are actively working on this issue at different levels. Their interests in signature modeling are discussed in the following summary: ?Biometric Recognition: Biometric recognition takes advantage of handwritten signature variability to automatically validate personal identity. Handwriting signatures are constructed by human movement as a consequence of brain activity [1] and this process is generally stable and PXD101 site over-learned during growth [2]. The rapid hand movement’s velocity profiles during the signature process have been studied in depth [3?]. Such models are currently being used for many applications such as to obtain the most relevant factors related to brain strokes [9, 10]. As a behavioral biometric, the legibility, speed, pen grip, pressure, style and error corrections are handwriting features affected by aging [11]. Experimental and practical studies have simulated aging effects [12]. ?Health: As the signing process involves highly complex, fine motor control to generate a mostly ballistic and over-learned movement, distortion or non-usual signature variability may indicate alteration of the motor or cognitive abilities and this is important for health applications [13, 14]. Nowadays, diagnosing and preventing neurodegenerative diseases is both a medical challenge and a major concern. Patients usually perform simple handwriting tests to detect Friedreich’s ataxia [15], spinocerebellar ataxia [16] or more frequently Parkinson’s [17], Alzheimer’s [18] or Huntington’s diseases. For instance, the correlation between handwriting degradation and the grade of Alzheimer’s disease [19] is high and seems to be accepted. The effect of tremor during the handwriting process provides information about degeneration [20]. Additionally, systems able to reproduce handwritten characters from recorded electromyography signals (EMGs) have been studied [21] as a measure to assist in the diagnosis of diseases or to study statistically the neuronal variations and their correlations [22, 23]. Handwriting analysis is an additional tool for detecting disease in its early stages through clinical assessment of grip kinetics and its variation [24]. ?Graphology: Graphology scrutinizes personality using a large set of features or symbols [25, 26]. Our signature subconsciously reflects our personality. Intra-personal variability studies generate consistent conclusions on the stability of signature features. Such features can be used, for instance, to estimate general personality, intelligence, (-)-Blebbistatin site social skill, emotions and social attitudes [27]. ?Forensics: “Signed, sealed, and delivered” is a traditional expression for the certification of documents [28]. Contracts, testaments, corporate tax returns, government legislation orPLOS ONE | DOI:10.1371/journal.pon.Drawn quickly and reflects more of the signer’s own personality, portraying dependencies of his or her neuromotor system’s ability and spatial cognitive map, among other factors. Also the text line design depends mainly on the signer’s name and the way the signers like to be introduced to others. For instance, let Peter Andrew Lee be a fictitious name. It could be written as P. A. Lee, Peter A. Lee and so on. The word and letter content defines the lexical part of a signature. Both parts give a particular structure or morphology to a signature. A number of disciplines require a deeper analysis of signatures for their specific fields of interests. Neurologists, graphologists, forensic and computer scientists are actively working on this issue at different levels. Their interests in signature modeling are discussed in the following summary: ?Biometric Recognition: Biometric recognition takes advantage of handwritten signature variability to automatically validate personal identity. Handwriting signatures are constructed by human movement as a consequence of brain activity [1] and this process is generally stable and over-learned during growth [2]. The rapid hand movement’s velocity profiles during the signature process have been studied in depth [3?]. Such models are currently being used for many applications such as to obtain the most relevant factors related to brain strokes [9, 10]. As a behavioral biometric, the legibility, speed, pen grip, pressure, style and error corrections are handwriting features affected by aging [11]. Experimental and practical studies have simulated aging effects [12]. ?Health: As the signing process involves highly complex, fine motor control to generate a mostly ballistic and over-learned movement, distortion or non-usual signature variability may indicate alteration of the motor or cognitive abilities and this is important for health applications [13, 14]. Nowadays, diagnosing and preventing neurodegenerative diseases is both a medical challenge and a major concern. Patients usually perform simple handwriting tests to detect Friedreich’s ataxia [15], spinocerebellar ataxia [16] or more frequently Parkinson’s [17], Alzheimer’s [18] or Huntington’s diseases. For instance, the correlation between handwriting degradation and the grade of Alzheimer’s disease [19] is high and seems to be accepted. The effect of tremor during the handwriting process provides information about degeneration [20]. Additionally, systems able to reproduce handwritten characters from recorded electromyography signals (EMGs) have been studied [21] as a measure to assist in the diagnosis of diseases or to study statistically the neuronal variations and their correlations [22, 23]. Handwriting analysis is an additional tool for detecting disease in its early stages through clinical assessment of grip kinetics and its variation [24]. ?Graphology: Graphology scrutinizes personality using a large set of features or symbols [25, 26]. Our signature subconsciously reflects our personality. Intra-personal variability studies generate consistent conclusions on the stability of signature features. Such features can be used, for instance, to estimate general personality, intelligence, social skill, emotions and social attitudes [27]. ?Forensics: “Signed, sealed, and delivered” is a traditional expression for the certification of documents [28]. Contracts, testaments, corporate tax returns, government legislation orPLOS ONE | DOI:10.1371/journal.pon.
